Login Register Cart 0
Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Computer-aided Drug Design Investigations for Benzothiazinone Derivatives Against Tuberculosis

Author(s): Jéssika O. Viana, Marcus T. Scotti and Luciana Scotti*

Volume 23, Issue 1, 2020

Page: [66 - 82] Pages: 17

DOI: 10.2174/1386207323666200117102316

Price: $65

Abstract

Background: Tuberculosis (Mycobacterium tuberculosis) is an infectious bacterial disease with the highest levels of mortality worldwide, presenting numerous cases of resistance. In silico studies, which elaborate chemical and biological models in computational tools and make it possible to interpret molecular characteristics, are among the methods used in the search for new drugs.

Objective: In this perspective, our aim was to use QSAR and molecular modeling to propose possible pharmacophores from benzothiazinone derivatives.

Methods: In this study, a set of 69 benzothiazinone derivatives, together with computational tools such as molecular descriptor analysis in chemometrics, metabolic prediction, and molecular coupling to 4 proteins: DprE1, InhA, PS, and DHFR important for the bacillus were investigated.

Results: The chemometric model computed in the Volsurf+ program presented good predictive values for both amphiphilicity and molecular volume. These are essential for biological activity. Metabolites from the cytochrome isoforms CYP3A4 and 2D6 interactions revealed coupling divergences which, noting that the metabolites did not present changes to the QSAR proposed pharmacophore structures, may be due to the reaction medium and existing differences in the benzothiazinone structures. Similarly, molecular docking with the four TB enzymes presented good interactions for the more active compounds. The fragments found using QSAR (being essential for biological activity) also presented as being essential for ligand-protein site interactions.

Conclusion: From the benzothiazinone derivative series evaluated, compound 11026134 presented the best profile in all study analyses, noting that the trifluoromethyl, nitro group, and piperazine fragment with aliphatic hydrocarbon groups are likely pharmacophores for the benzothiazinones studied.

Keywords: Antitubercular drugs, benzothiazinones, QSAR, molecular docking, metabolic prediction, pharmacophore.

« Previous Next »
[1]
Sensi, P.; Grass, I.G.G. Antimycobacterial Agents.Burger's medicinal chemistry and drug discovery; Wolff, M.E,. Amer. J. Therap , 1996, 3, p.(8), 608.
[2]
Brosch, R.; Gordon, S.V.; Marmiesse, M.; Brodin, P.; Buchrieser, C.; Eiglmeier, K.; Garnier, T.; Gutierrez, C.; Hewinson, G.; Kremer, K.; Parsons, L.M.; Pym, A.S.; Samper, S.; van Soolingen, D.; Cole, S.T. A new evolutionary scenario for the Mycobacterium tuberculosis complex. Proc. Natl. Acad. Sci. USA, 2002, 99(6), 3684-3689.
[http://dx.doi.org/10.1073/pnas.052548299] [PMID: 11891304]
[3]
World Health Organization. http://apps.who.int/iris/bitstream/ handle/10665/274453/9789241565646-eng.pdf?ua=12018.
[4]
Makarov, V.; Manina, G.; Mikusova, K.; Möllmann, U.; Ryabova, O.; Saint-Joanis, B.; Dhar, N.; Pasca, M.R.; Buroni, S.; Lucarelli, A.P.; Milano, A.; De Rossi, E.; Belanova, M.; Bobovska, A.; Dianiskova, P.; Kordulakova, J.; Sala, C.; Fullam, E.; Schneider, P.; McKinney, J.D.; Brodin, P.; Christophe, T.; Waddell, S.; Butcher, P.; Albrethsen, J.; Rosenkrands, I.; Brosch, R.; Nandi, V.; Bharath, S.; Gaonkar, S.; Shandil, R.K.; Balasubramanian, V.; Balganesh, T.; Tyagi, S.; Grosset, J.; Riccardi, G.; Cole, S.T. Benzothiazinones kill Mycobacterium tuberculosis by blocking arabinan synthesis. Science, 2009, 324(5928), 801-804.
[http://dx.doi.org/10.1126/science.1171583] [PMID: 19299584]
[5]
Makarov, V.; Lechartier, B.; Zhang, M.; Neres, J.; van der Sar, A.M.; Raadsen, S.A.; Hartkoorn, R.C.; Ryabova, O.B.; Vocat, A.; Decosterd, L.A.; Widmer, N.; Buclin, T.; Bitter, W.; Andries, K.; Pojer, F.; Dyson, P.J.; Cole, S.T. Towards a new combination therapy for tuberculosis with next generation benzothiazinones. EMBO Mol. Med., 2014, 6(3), 372-383.
[http://dx.doi.org/10.1002/emmm.201303575] [PMID: 24500695]
[6]
Yildirim, M.A.; Goh, K.I.; Cusick, M.E.; Barabási, A.L.; Vidal, M. Drug-target network. Nat. Biotechnol., 2007, 25(10), 1119-1126.
[http://dx.doi.org/10.1038/nbt1338] [PMID: 17921997]
[7]
Lavecchia, A.; Di Giovanni, C. Virtual screening strategies in drug discovery: a critical review. Curr. Med. Chem., 2013, 20(23), 2839-2860.
[http://dx.doi.org/10.2174/09298673113209990001] [PMID: 23651302]
[8]
Azad, C.S.; Bhunia, S.S.; Krishna, A.; Shukla, P.K.; Saxena, A.K. Novel glycoconjugate of 8‐fluoro norfloxacin derivatives as gentamicin‐resistant Staphylococcus aureus inhibitors: synthesis and molecular modelling studies. Chem. Biol. Drug Des., 2015, 86(4), 440-446.
[http://dx.doi.org/10.1111/cbdd.12503] [PMID: 25546316]
[9]
Golbraikh, A.; Tropsha, A. QSAR/QSPR Revisited.Chemoinformatics: Basic Concepts and Methods; John Wiley & Sons, 2018.
[http://dx.doi.org/10.1002/9783527816880.ch12]
[10]
Dearden, J.C. The history and development of quantitative structure-activity relationships (QSAR).Oncology: breakthroughs in research and practice; IGI Global, 2017.
[http://dx.doi.org/10.4018/978-1-5225-0549-5.ch003]
[11]
Ferreira, L.G.; Dos Santos, R.N.; Oliva, G.; Andricopulo, A.D. Molecular docking and structure-based drug design strategies. Molecules, 2015, 20(7), 13384-13421.
[http://dx.doi.org/10.3390/molecules200713384] [PMID: 26205061]
[12]
Pandit, D.; So, S.S.; Sun, H. Enhancing specificity and sensitivity of pharmacophore-based virtual screening by incorporating chemical and shape features--a case study of HIV protease inhibitors. J. Chem. Inf. Model., 2006, 46(3), 1236-1244.
[http://dx.doi.org/10.1021/ci050511a] [PMID: 16711743]
[13]
Hehre, W.J. Spartan Software; Wavefunction. Inc.: Irvine, 2000.
[14]
Allinger, N.L.; Yuh, Y.H.; Lii, J.H. Molecular mechanics. The MM3 force field for hydrocarbons. 1. J. Am. Chem. Soc., 1989, 111(23), 8551-8566.
[http://dx.doi.org/10.1021/ja00205a001]
[15]
Dewar, M.J.S.; Zoebisch, E.G.; Healy, E.F.; Stewart, J.J.P. Development and use of quantum mechanical molecular models. 76. AM1: a new general-purpose quantum mechanical molecular model. J. Am. Chem. Soc., 1985, 107(13), 3902-3909.
[http://dx.doi.org/10.1021/ja00299a024]
[16]
Cruciani, G.; Crivori, P.; Carrupt, P.A.; Testa, B. Molecular fields in quantitative structure–permeation relationships: the VolSurf approach. J. Mol. Struct. THEOCHEM, 2000, 503(1), 17-30.
[http://dx.doi.org/10.1016/S0166-1280(99)00360-7]
[17]
Cruciani, G.; Pastor, M.; Guba, W. VolSurf: a new tool for the pharmacokinetic optimization of lead compounds. Eur. J. Pharm. Sci., 2000, 11(Suppl. 2), S29-S39.
[http://dx.doi.org/10.1016/S0928-0987(00)00162-7] [PMID: 11033425]
[18]
Abdi, H.; Williams, L.J. Principal component analysis. Wiley Interd. Rev.: Comp. Stat, 2010, 2, 433-459.
[http://dx.doi.org/10.1002/wics.101]
[19]
Geladi, P.; Kowalski, B.R. Partial least-squares regression: a tutorial. Anal. Chim. Acta, 1986, 185, 1-17.
[http://dx.doi.org/10.1016/0003-2670(86)80028-9]
[20]
Cruciani, G.; Carosati, E.; De Boeck, B.; Ethirajulu, K.; Mackie, C.; Howe, T.; Vianello, R. MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist. J. Med. Chem., 2005, 48(22), 6970-6979.
[http://dx.doi.org/10.1021/jm050529c] [PMID: 16250655]
[21]
Cruciani, G.; Baroni, M.; Benedetti, P.; Goracci, L.; Fortuna, C.G. Exposition and reactivity optimization to predict sites of metabolism in chemicals. Drug Discov. Today. Technol., 2013, 10(1), e155-e165.
[http://dx.doi.org/10.1016/j.ddtec.2012.11.001] [PMID: 24050245]
[22]
Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The protein data bank. Nucleic Acids Res., 2000, 28(1), 235-242.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[23]
Molegro Virtual Docker. 0.1.; CLC Bio Company., Molegro ApS Aarhus, Denmark ; Vol. 6. 2013.
[24]
Plewczynski, D.; Łaźniewski, M.; Augustyniak, R.; Ginalski, K. Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database. J. Comput. Chem., 2011, 32(4), 742-755.
[http://dx.doi.org/10.1002/jcc.21643] [PMID: 20812323]
[25]
Thomsen, R.; Christensen, M.H. MolDock: a new technique for high-accuracy molecular docking. J. Med. Chem., 2006, 49(11), 3315-3321.
[http://dx.doi.org/10.1021/jm051197e] [PMID: 16722650]
[26]
Makarov, V.; Neres, J.; Hartkoorn, R.C.; Ryabova, O.B.; Kazakova, E.; Šarkan, M.; Huszár, S.; Piton, J.; Kolly, G.S.; Vocat, A.; Conroy, T.M.; Mikušová, K.; Cole, S.T. 8-Pyrrole-benzothiazinones non-covalent inhibitors of DprE1 from Mycobacterium tuberculosis. Antimicrob. Agents Chemother., 2015, 59(8), 4446-4452.
[http://dx.doi.org/10.1128/AAC.00778-15] [PMID: 25987616]

Rights & Permissions Print Cite
Article Metrics
31
3
© 2024 Bentham Science Publishers | Privacy Policy